Tissue heating and ablation systems and methods which predict maximum tissue temperature

ABSTRACT

Systems and methods heat or ablate body tissue by positioning an electrode to transmit heat or ablation energy to a tissue region. The systems and methods measure a first temperature using a temperature sensing element associated with the electrode. The systems and methods also measure a second temperature using a temperature sensing element associated with the electrode. The systems and methods process at least one of the first and second temperatures to derive a prediction of maximum temperature of the tissue region. The systems and methods generate an output that controls the transmission of the heating or ablation energy based, at least in part, upon the maximum tissue temperature prediction.

FIELD OF THE INVENTION

[0001] In a general sense, the invention is directed to systems andmethods for creating lesions in the interior regions of the human body.In a more particular sense, the invention is directed to systems andmethods for ablating heart tissue for treating cardiac conditions.

BACKGROUND OF THE INVENTION

[0002] Physicians frequently make use of catheters today in medicalprocedures to gain access into interior regions of the body. In someprocedures, the catheter carries an energy transmitting element on itsdistal tip to ablate body tissues.

[0003] In such procedures, the physician must establish stable anduniform contact between the energy transmitting element and the tissueto be ablated. Upon establishing contact, the physician must thencarefully apply ablating energy to the element for transmission to thetissue.

[0004] The need for precise control over the transmission of ablationenergy is especially critical during catheter-based procedures forablating heart tissue. These procedures, called electrophysiologytherapy, are becoming increasingly more widespread for treating cardiacrhythm disturbances, called arrhythmias. Cardiac ablation procedurestypically use radio frequency (RF) energy to form a lesion in hearttissue.

[0005] The principal objective of the invention is to provide systemsand methods for monitoring and reliably controlling the application ofenergy to ablate body tissue, thereby providing therapeutic results in aconsistent and predictable fashion.

SUMMARY OF THE INVENTION

[0006] The invention provides systems and methods that provide reliablecontrol over tissue heating and ablation procedures using temperaturesensing.

[0007] The systems and methods heat or ablate body tissue by positioningan electrode to transmit heat or ablation energy to a tissue region. Thesystems and methods measure a first temperature using a temperaturesensing, element associated with the electrode. The systems and methodsalso measure a second temperature using a temperature sensing elementassociated with the electrode. The systems and methods process at leastone of the first and second temperatures to derive a prediction ofmaximum temperature of the tissue region.

[0008] In a preferred embodiment, the systems and methods generate anoutput that controls the transmission of the heating or ablation energybased, at least in part, upon the maximum tissue temperature prediction.

[0009] Other features and advantages of the inventions are set forth inthe following Description and Drawings, as well as in the appendedclaims.

BRIEF DESCRIPTION OF THE DRAWINGS

[0010]FIG. 1 is a perspective view of a system for ablating tissue thatcomprises an energy emitting electrode and associated energy generator;

[0011]FIGS. 2, 3 and 4 are, respectively, an elevated side view, an endview, and a side section view (taken along line 4-4 in FIG. 3) of theelectrode associated with the system shown in FIG. 1, the electrodehaving two temperature sensing elements;

[0012]FIG. 5 is a schematic view of the generator for supplying energyto the electrode in the system shown in FIG. 1, the generator using aspecialized modified PID control technique to maintain a desired settemperature by altering power in response to a prediction of maximumtissue temperature;

[0013]FIG. 6 is a schematic view of a device used to experimentallydetermine the relationship between maximum tissue temperature and thetemperatures sensed by two sensing elements carried by an electrode;

[0014]FIG. 7A is a graph presenting a comparison, for anelectrode-tissue angle of 90°, of the temperature variations with timewhen the actual highest tissue temperature controlled the application ofradio frequency energy compared when a predicted maximum tissuetemperature, calculated according to the invention, was used as thecontrol input;

[0015]FIG. 7B is a graph presenting a comparison of applied power versustime under the same conditions set forth in FIG. 7A;

[0016]FIG. 8A is a graph presenting a comparison, for anelectrode-tissue angle of 0°, of the temperature variations with timewhen the actual highest tissue temperature controlled the application ofradio frequency energy compared when a predicted maximum tissuetemperature, calculated according to the invention, was used as thecontrol input;

[0017]FIG. 8B is a graph presenting a comparison of applied power versustime under the same conditions set forth in FIG. 8A;

[0018]FIG. 9 is a schematic view of the implementation of a neuralnetwork predictor to predict maximum tissue temperature;

[0019]FIG. 10 is a representative single-perception network that can beused to predict maximum tissue temperature according to the invention;

[0020]FIG. 11 is a graph presenting a comparison, for anelectrode-tissue angle of 90°, of the temperature variations with timewhen the actual highest tissue temperature controlled the application ofradio frequency energy compared when the predicted maximum tissuetemperature output of the network shown in FIG. 10 was used as thecontrol input;

[0021]FIG. 12 is a schematic view of the implementation of fuzzy logicto predict maximum tissue temperature; and

[0022]FIG. 13 is a flexible, multiple electrode element with multipletemperature sensing elements that can be used to predict maximum tissuetemperature according to the invention;

[0023]FIG. 14 is an electrode with multiple temperature sensingelements, and a heating element to heat the electrode, which can be usedto predict maximum tissue temperature according to the invention;

[0024]FIG. 15 is an alternative embodiment of an electrode with multipletemperature sensing elements and a heating element which can be used topredict maximum tissue temperature according to the invention;

[0025]FIG. 16 is a system including an electrode like that shown ineither FIG. 14 or FIG. 15, which can be used to predict maximum tissuetemperature according to the invention; and

[0026]FIGS. 17 and 18 are schematic views of a system for controllingthe application of ablation energy to multiple electrodes using multiplepredicted maximum tissue temperature inputs.

[0027] The invention may be embodied in several forms without departingfrom its spirit or essential characteristics. The scope of the inventionis defined in the appended claims, rather than in the specificdescription preceding them. All embodiments that fall within the meaningand range of equivalency of the claims are therefore intended to beembraced by the claims.

DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0028]FIG. 1 shows a system 10 for ablating human tissue that embodiesthe features of the invention.

[0029] In the illustrated and preferred embodiment, the system 10includes a generator 12 that delivers radio frequency energy to ablatetissue. Of course, other types of energy can be generated for tissueablating purposes.

[0030] The system 10 also includes a steerable catheter 14 carrying aradio frequency transmitting ablation electrode 16. In the illustratedembodiment, the ablation electrode 16 is made of platinum.

[0031] In the illustrated embodiment, the system 10 operates in aunipolar mode. In this arrangement, the system 10 includes a skin patchelectrode that serves as an indifferent second electrode 18. In use, theindifferent electrode 18 attaches to the patient's back or otherexterior skin area.

[0032] Alternatively, the system 10 can be operated in a bipolar mode.In this mode, the catheter 14 carries both electrodes.

[0033] The system 10 can be used in many different environments. Thisspecification describes the system 10 when used to provide cardiacablation therapy.

[0034] When used for this purpose, a physician steers the catheter 14through a main vein or artery (typically the femoral vein or artery)into the interior region of the heart that is to be treated. Thephysician then further manipulates the catheter 14 to place theelectrode 16 into contact with the tissue within the heart that istargeted for ablation. The user directs radio frequency energy from thegenerator 12 into the electrode 16 to ablate and form a lesion on thecontacted tissue.

[0035] In the embodiment shown in FIG. 1, the catheter 14 includes ahandle 20, a catheter body 22, and a distal tip 24, which carries theelectrode 16.

[0036] The handle 20 encloses-a steering mechanism 26 for the cathetertip 24. A cable 28 extending from the rear of the handle 20 to connectthe catheter 14 to the generator 12 for conveying radio frequency energyto the ablation electrode 16 via a signal wire 29 (see FIG. 4).

[0037] Left and right steering wires 54 (see FIG. 4) are connected to asteering spring 52 at the tip of the catheter body 22. The steeringwires extend through the catheter body 22 to interconnect the steeringmechanism 26 in the handle 20 (see FIG. 1). Rotating the steeringmechanism 26 to the left pulls on the left steering wire, causing thespring 52 and tip 24 to bend to the left. In the same way, rotating thesteering mechanism 26 to the right causes the spring 52 and tip 24 tobend to the right. In this way, the physician steers the ablationelectrode 16 into contact with the tissue to be ablated.

[0038] Further details of this and other types of steering mechanismsfor the ablating element 10 are shown in Lunquist and Thompson U.S. Pat.No. 5,254,088, which is incorporated into this Specification byreference.

I. Multiple Temperature Sensing

[0039] As FIGS. 2 to 4 show, the ablation electrode 16 carries twotemperature sensing elements 30 and 32. As will be described in greaterdetail later, the power that the generator 12 applies to the electrode16 is set, at least in part, by the temperature conditions sensed by theelements 30 and 32.

[0040] As best shown FIGS. 3 and 4, the ablation electrode 16 includesan interior well 34 extending through its center. The two temperaturesensing elements 30 and 32 occupy this well 34.

[0041] In the illustrated embodiment, the first temperature sensingelement 30 is carried within a cap 42 at the distal extremity of thewell 34. In use, the sensing element 30 is intended to make thermalconductive contact with tissue, to thereby sense tissue temperature.

[0042] Lead wires 38 extend from the sensing element 30 through thecatheter body 22 into the catheter handle 20. There, the lead wires 38electrically couple to the cable 28 for connection to the generator 12.The lead wires 38 transmit the tissue temperature signals from thetemperature sensing element 30 to the generator 12.

[0043] In the illustrated and preferred embodiment, the sensing element30 comprises a conventional small bead thermistor 40. For example, a0.55 mm bead thermistor commercially available from Thermometrics(Edison, N.J.), Part Number AB6B2-GC16KA143E/37° C-A can be used.

[0044] The sensing element 30 and lead wires 38 are electricallyinsulated from the surrounding ablation electrode 16. For this purpose,electrically insulating potting compound, such as heavy isomid,cyanoacrylate adhesive, silicon rubber RTV adhesive, polyurethane,epoxy, or the like, encapsulates the thermistor bead 40 in conventionalfashion. The lead wires 38 are likewise enclosed in electricallyinsulating sheaths made from, for example, polyimide material, althoughother conventional electrical insulating materials also can be used.

[0045] The cap 42 is made from a thermal conducting material having ahigh thermal conductivity that is at least 1.0 watt (W) per meter (m)Kelvin (K), or 1.0 W/m K. Metallic materials like stainless steel, gold,silver alloy, platinum, copper, nickel, titanium, aluminum, andcompositions containing stainless steel, gold, silver, platinum, copper,nickel, titanium, and aluminum possess this degree of thermalconductivity. The encapsulated thermistor bead 40 is preferably pottedwithin the cap 42 using an electrically insulating epoxy having anenhanced thermal conductivity that is at least 1.0 W/m K. The inclusionof a metallic paste (for example, containing aluminum oxide) in astandard epoxy material will provide this enhanced thermal conductivity.

[0046] The cap 42 is fitted within the well 34 of the electrode 16 withits distal end 44 making thermal conductive contact with the tissue. Thehigh thermal conductivity of the cap material assures that the cap 42will quickly reach an equilibrium temperature close to that of thetissue it contacts.

[0047] In the illustrated and preferred embodiment, a thermal andelectrically insulating barrier 46 forms an interface between theinterior wall of the well 34 and the side of the cap 42 that occupiesit. In a preferred embodiment, the barrier 46 comprises polyamideadhered about the sidewall of the cap 42 using FMD-14 to serve as anelectrical insulator. The barrier 46 also comprises polyester shrinktubing secured by heat shrinking about the polyamide to serve as athermal insulator. In the illustrated and preferred embodiment, thethermistor-containing cap 42 and associated barrier 46 are affixed andpotted within the electrode well using cyanoacrylate FMD-13 (LoctiteCorporation, Newington, Conn.).

[0048] The thermal conducting cap 42 creates an isothermal conditionabout the sensing element 30 close to the actual temperature of thetissue it contacts. Furthermore, the cap 42, being substantiallyisolated from thermal conductive contact with the electrode 16, retainsthis isothermal condition about sensing element 30, preventing itsdissipation by the thermal mass of the electrode 16. Further details ofthe use and construction of the thermal conducting cap 42 are found incopending U.S. patent application Ser. No. 08/432,321, filed May 1,1995, and entitled “Systems and Apparatus for Sensing Temperature inBody Tissue”, which is incorporated herein by reference.

[0049] The second temperature sensing element 32 carried within the well34 is connected by soldering or by thermal conductive adhesive in directthermal conductive contact with the thermal mass of the electrode 16.While transmitting radio-frequency energy to heat surrounding tissue,the electrode 16 is heated by thermal conduction from the heated tissue.In use, the second sensing element 32 is intended to sense thetemperature of the electrode 16 due to conductive heat transfer.

[0050] In the illustrated and preferred embodiment, the sensing element32 also comprises a conventional small bead thermistor 48, as alreadydescribed in connection with the sensing element 30. Also, like thesensing element 30, the sensing element 32 is electrically insulatedfrom the electrode 16 by encapsulation in an electrically insulatingpotting compound, as also already described.

[0051] The thermistor 48 also has associated lead wires 50, which extendthrough the catheter body 22 and handle 20 to the cable 28. The cable 28transmits the electrode temperature signals from the temperature sensingelement 32 to the generator 12.

[0052] It should be appreciated that the first temperature sensingelement 30 need not be positioned in thermal conductive contact withtissue. The first element 30 can, like the second element 32, bepositioned in thermal conductive contact with the electrode 16. It isalso not necessary that one or both sensing elements 30 and 32 be indirect thermal conductive contact with the electrode 16. The inventionrequires only that the two temperature sensing elements 30 and 32 bepositioned relative to the electrode 16 in a spaced apart condition tomeasure a meaningful spatial temperature gradient at thetissue-electrode interface.

[0053] It should also be appreciated that the electrode 16 need not bein direct contact with tissue. Laser and microwave transmittingelectrodes can carry the spaced apart temperature sensing elements 30and 32 and perform tissue ablation according to invention withoutcontacting the ablated tissue.

[0054] The apparatus and methods that embody the features of theinvention are well suited for use in the field of cardiac ablation,which the preferred embodiments exemplify. Still, the invention isapplicable for use in tissue heating applications, as well. For example,the various aspects of the invention have application in procedures forablating or heating tissue in the prostrate, brain, gall bladder,uterus, and other regions of the body, using systems that are notnecessarily catheter-based.

[0055] It should be appreciated that other types of temperature sensingelements can also be used. For example, a thermocouple could be used asthe temperature sensing element. In a preferred implementation, thethermocouples are constructed by either spot welding or by laserstripping and welding the different metals together to form thethermocouple junction. When a thermocouple serves as the temperaturesensing element, a reference thermocouple must be used. The referencethermocouple may be placed in the handle 20, generator 12, or exposed tothe blood pool in the manner disclosed in copending U.S. patentapplication Ser. No. 08/286,937, filed Aug. 8, 1994, and entitled“Systems and Methods for Sensing Temperature Within the Body.”

[0056] Electrical insulation is also required when thermocouples areused as the temperature sensors. For example, the thermocouple junctioncan be placed in a thermally conducting epoxy inside a polyester sleeve.In a preferred implementation, the thermocouple junction is placed in UVmodified acrylic adhesive 330 (Loctite Corporation, Newington, Conn.)within a shrink polyester sleeve, which is then shrunk to fit tightlyabout the thermocouple junction and wires. To reduce electricalinterference, the thermocouple wires are also preferably electricallyshielded and twisted together.

II. THE RF GENERATOR

[0057] As FIG. 5 shows, the generator 12 includes a radio frequencypower source 56 connected through a main isolation transformer 58 tooutlet and return lines 60 and 62. Outlet line 60 leads to the ablationelectrode 16. Return line 62 leads from the indifferent electrode 18.

[0058] In the illustrated embodiment, when used for cardiac ablation,the power source 56 is typically conditioned to deliver up to 150 wattsof power at a radio frequency of 500 kHz.

[0059] The generator 12 further includes a temperature acquisitionsystem 64, a temperature processing element 66, a demand power processor68, and a converter 70. These components comprise a feedback loop, whichcouples the two temperature sensing elements 30 and 32 to the source 56for making applied radio-frequency energy responsive to sensedtemperature conditions.

[0060] The temperature acquisition system 64 is coupled to the twotemperature sensing elements 30 and 32. The system 64 continuouslysamples at prescribed time periods, t, the analog signals generated bythe sensing elements 30 and 32 based upon sensed temperature conditions.The system 64 converts the separate analog signals of the sensingelements 30 and 32 into individual, proportional digital signals,respectively tissue temperature T₁(t) and electrode temperature T₂(t).

[0061] The temperature processing element 66 is coupled to thetemperature acquisition system 64 to receive as input the digitalsignals tissue temperature T₁(t) and electrode temperature T₂ (t). Theprocessing element 66 applies prescribed criteria to these actualtemperature signals to derive, for the sampled time interval, aprediction of the hottest tissue temperature present in the tissueregion in the vicinity of the electrode 16, T_(pred)(t).

[0062] The demand power processor 68 periodically compares T_(pred)(t)to a set temperature value T_(SET). The set temperature value T_(SET)can be inputted by the physician through an interface 72. The settemperature value T_(SET) represents the maximum tissue temperature thephysician wants to maintain at the ablation site. The value T_(SET) canbe established in other ways. For example, the value T_(SET) can varyover time to define a set temperature curve.

[0063] The set temperature value T_(SET) selected depends upon thedesired therapeutic characteristics of the lesion. Typical therapeuticlesion characteristics are the surface area of the tissue that isablated and depth of the ablation. Typically, the set temperatureT_(SET) is in the range of 50 to 90 degrees C.

[0064] Based upon this comparison, and preferably taking into accountthe magnitude of the instantaneous power P(t) supplied to the ablatingelectrode 16, the processor 68 derives the demand power outputP_(DEMAND)(t). The demand power output P_(DEMAND)(t) represents themagnitude of the radio frequency power that should be supplied to theablating electrode 16 to establish or maintain the desired localtemperature condition T_(SET) at the ablating electrode 16. By takinginto account the magnitude of the instantaneous power P(t), theprocessor 68 assures that a prescribed maximum power level P_(MAX) isnot exceeded.

[0065] The manner in which the processor 68 derives P_(DEMAND)(t) canvary. For example, it can employ proportional control principles,proportional integral derivative (PID) control principles, adaptivecontrol, neural network, and fuzzy logic control principles.

EXAMPLE 1

[0066] The following Example 1 shows an exemplary core PID controlalgorithm that the processor 68 can employ for controlling power basedupon predicted tissue temperature.

[0067] In this example, K_(p), K_(d), and K_(i) are, respectively, theproportional, derivative, and integral coefficients of the PID algorithmused for controlling power based on predicted tissue temperature. Thesame algorithm was used to control actual tissue temperature in thecomparisons presented in FIGS. 7 A/B and 8 A/B, to be discussed ingreater detail later.

[0068] In this algorithm, the power at time t+1 is controlled based uponthe difference between the temperature and the set temperature at timest, t−1, and t−2 (expressed in Kelvin or degrees Celsius), as follows:

power (t+1)=7W*{K _(p)*(T(t)−T _(SET))+K _(d)*[(T(t)−T _(SET))−(T(t−1)−T _(SET))]+K _(j)*[(T(t)−T _(SET))+(T(t−1)−T _(SET))+(T(t−2)−T_(SET))]}

[0069] Data collected from the finite element analysis presented below(in Section III(A)) demonstrates that the following coefficients can beused:

[0070] K_(p)=0,04

[0071] K_(i)=0.005

[0072] K_(d)=0.008

[0073] The multiplier “7W” appearing in the above algorithm reflectsthat the finite element analysis, from which the coefficients werederived, computed the power-to-temperature transfer function of themodeled system at a 7 watt (W) level.

[0074] The foregoing example sets forth the core of the controlalgorithm for deriving p(I) (i.e., P_(Demand), based upon a fixed valueof T_(SET). The algorithm can include other auxiliary features.

[0075] For example, T_(SET) can be expressed as a function with respectto time, which can be linear, or nonlinear, or both.

[0076] As another example, P_(Demand) derived by the algorithm can becompared to a maximum power condition. Should P_(Demand) exceed themaximum power condition, the controller 68 blocks passage of P_(Demand)and instead commands a preestablished low power condition untilP_(Demand) becomes less than the maximum power.

[0077] Other representative implementations are disclosed in copendingpatent application Ser. No. 08/266,934, filed Jun. 27, 1994, andentitled “Tissue Heating and Ablation Systems and Methods UsingPredicted Temperature for Monitoring and Control.”

[0078] The converter 70 derives a command voltage signal V_(DEMAND)(t)based upon the demand power output P_(DEMAND)(t). The command voltagesignal V_(DEMAND)(t)adjusts the amplitude of the voltage V_((t))supplied to the source 56 to thereby adjust P_((t)) Alternatively, theconverter 70 could derive a command current signal I_(DEMAND(t)) basedupon the demand power output P_(DEMAND)(t) to adjust the amplitude ofthe current supplied to the source 56, achieving the same results.

[0079] The manner in which the converter 70 generates V_(DEMAND)(t) toadjust P(t) can vary. For example, the converter 70 can employproportional control principles, proportional integral derivative (PID)control principles, neural network, fuzzy logic, and adaptive controlprinciples. Representative implementations are disclosed in copendingpatent application Ser. No. 08/266,934, filed Jun. 27, 1994, andentitled “Tissue Heating and Ablation Systems and Methods UsingPredicted Temperature for Monitoring and Control.”

III. Deriving T_(PRED)(t) A. Prediction Based Upon An AnalyticalFunction

[0080] The quantity T_(PRED) can be expressed in terms of an analyticalfunction f (T₁, T₂), which sets forth, for a given electrode geometry,the variation of hottest tissue temperature T_(MAX) with sensed tissuetemperature T₁ and sensed electrode temperature T₂. The function isdetermined for a given electrode geometry by tabulating in vitro or invivo results, measuring T₁, T₂, and T_(MAX), and generating finiteelement models for the same electrode geometries to estimate T_(PRED),until the modeled T_(PRED)≈measured T_(MAX).

EXAMPLE 2 Determining an Analytical T_(PRED) Function

[0081] A three-dimensional finite element model is created for an 8Fdiameter/5 mm long radio frequency ablation electrode placed in a bloodpool in contact with an approximately 4 cm thick rectangular slice ofcardiac tissue at tissue-electrode angles of 0° and 90°. The electrodehas two temperature sensing elements, as shown in FIGS. 2 to 4, oneelectrically and thermally isolated at the tip for sensing tissuetemperature and the other electrically isolated but in thermalconductive contact with the electrode for sensing electrode temperature.The tip of the electrode extends about 1.3 mm into the tissue. Theoverall volume is a parallelpiped 8 cm long, 4 cm wide, and 4 cm thick.The model has 8144 nodes, using hexahedral elements and a nonuniformmesh.

[0082] The current density boundary conditions are set at the electrode,so that the maximum tissue temperature (T_(MAX)) reaches about 95° C.after 120 seconds.

[0083] COSMOS is used on a Hewlett Packard workstation to perform theelectrical-thermal, transient analyses for 120 seconds. The analysesestimate the function that defines the relationship between T₁, T₂, andthe predicted maximal tissue temperature.

[0084] The model results are corroborated with experimental dataacquired using the apparatus shown in FIG. 6. A 4 cm thick slice ofbovine heart H is fixed in good contact with a 144 cm² patch electrodeEP inside a tank T filled with saline at 37° C. An ablation catheter Ccarrying an 8F diameter/5 mm long electrode E is placed in contact withthe tissue surface H at an angle of 0° and 90°. A 0.55 mm beadthermistor TM1 is placed at the electrode tip (to sense T₁), another0.55 mm bead thermistor TM2 is placed within the electrode (to senseT₂), and a third thermistor TM3 is placed in the cardiac tissue H about0.5 mm beneath the electrode tip, which corresponds to the hottesttissue temperature region predicted by the finite element simulations.The thermistor readings are acquired at a sampling rate of 20 ms byLabView running on a Power Mac. A 500 kHz sinusoidal signal is appliedbetween the ablation and indifferent electrodes using a 150 W RFablation system AS. The delivered RF power (P) is kept constant at 7 W.

[0085] Using the above-described methodology, the following function wasdetermined to yield good results for the 8F/5 mm electrode:

T_(pred)(t)=4.03*T₁(t)−2.97*T₂(t)

[0086] The above-described methodology can be used to derive thefunction for other electrode geometries, as well.

[0087] The behavior of the function for an 8F/5 mm electrode isacceptable at both tissue-electrode angles of 0° and 90°. FIG. 7Apresents a comparison, for an electrode-tissue angle of 90°, of thetemperature variations with time when the actual highest tissuetemperature controlled the application of radio frequency energycompared when T_(pred), calculated according to the above function, wasused as the control input, using the PID control algorithm like thatdisclosed above. FIG. 7B presents a comparison of applied power versustime under the same conditions. FIGS. 8A and 8B present similarcomparisons for a tissue-electrode angle of 0°. Both comparisons showthat any overshoot and settling time will, in time, converge to zero.

[0088] Since the data reflected in FIGS. 7B and 8B are based upon afinite element analysis conducted at 7 W, the numbers on the y-axisshown in FIGS. 7B and 8B should be multiplied by 7 W to obtain the truepower levels.

[0089]FIGS. 7B and 8B also show that keeping the temperature at a fixedset value requires a continuous, slow ramping down of applied power.This is because the temperature of heart tissue, when heated at aconstant applied power, does not actually reach a steady state below100° C. Instead, maximum tissue temperature is observed to continuouslyincrease at a slow rate until it reaches 100° C., at which timemicro-explosions occur. This rate is defined by the expression:$\frac{\partial T}{\partial t} = {{\frac{1}{\rho \cdot c}{j \cdot E}} \succ 0}$

[0090] where:

[0091] T is tissue temperature.

[0092] t is time.

[0093] ∂T/∂t is the first temporal derivative of the temperature.

[0094] ρ is tissue density.

[0095] c is heat capacity of the tissue.

[0096] j is current density.

[0097] E is electric field intensity.

[0098] As FIGS. 7B and 8B show, there is, for a given electrode geometryand electrode-tissue angle, a determinable rate at which power decreasesto maintain a predicted maximum tissue temperature. In FIG. 7B, the rateis 0.008 W/sec for an 8F/5 mm electrode and a 90° tissue-electrodeangle. In FIG. 8B, the rate is 0.003 W/sec for an 8F/5 mm electrode anda 0° tissue-electrode angle. The temperature processor 66 can ascertainthis power-down rate upon deriving T_(PRED)(t) using preestablishedlook-up tables. The processor 66 can generate the power-down rate asoutput to the demand power processor 68, instead of T_(PRED)(t). Theprocessor 68 would control predicted tissue temperature by ramping downthe power transmitted by the electrode based upon the power-down rate.

B. Prediction Based Upon Neural Networks

[0099] The dependence of maximum tissue temperature on T₁ and T₂ canalso be approximated using neural networks. FIG. 9 shows animplementation of a neural network predictor 300, which receives asinput the temperatures T₁(t) and T₂(t) sensed at the electrode. Thepredictor 300 outputs a predicted temperature of the hottest tissueregion T_(PRED)(t).

[0100] The predictor 300 uses a two-layer neural network, although moreor less hidden layers could be used. As shown in FIG. 9, the predictor300 includes first and second hidden layers and four neurons, designatedN(L,X), where L identifies the layer 1 or 2 and X identifies a neuron onthat layer. The first layer (L=1) has three neurons (X =1 to 3), asfollows N(1,1); N(1,2); and N(1,3). The second layer (L=2) comprisingone output neuron (X=1), designated N(2,1).

[0101] Temperature readings from the multiple sensing elements areweighed and inputted to each neuron N(1,1); N(1,2); and N(1,3) of thefirst layer. FIG. 9 represents the weights as W^(L)(k,N), where L=1; kis the input sensor order; and N is the input neuron number 1, 2, or 3of the first layer.

[0102] The output neuron N(2,1) of the second layer receives as inputsthe weighted outputs of the neurons N(1,1); N(1,2); and N(1,3). FIG. 9represents the output weights as W^(L)(O,X), where L=2; O is the outputof neuron 1, 2, or 3 of the first layer; and X is the input neuronnumber of the second layer. Based upon these weighted inputs, the outputneuron N(2,1) predicts T_(PRED)(t). Alternatively, a sequence of pastreading samples from each sensor could be used as input. By doing this,a history term would contribute to the prediction of the hottest tissuetemperature.

[0103] The predictor 300 must be trained on a known set of datacontaining the temperature of the sensing elements T₁ and T₂ and thetemperature of the hottest region, which have been previously acquiredexperimentally in the manner set forth in the foregoing example. Forexample, using a back-propagation model, the predictor 300 can betrained to predict the known hottest temperature of the data set withthe least mean square error. Once the training phase is completed, thepredictor 300 can be used to predict T_(PRED)(t)

EXAMPLE 3 Tissue Temperature Prediction Using Neural Networks

[0104]FIG. 10 shows a single perceptron network 302 with inputsT_(TIP)(t) and T_(CENTER)(t) corresponding with temperatures sensed bysensing element 30 and sensing element 32, respectively. The output isT_(PRED)(t). Weights w₁ and w₂ and bias θ(t) are used.

[0105] This network 302 computes T_(PRED)(t) as follows:

u(t)=w ₁*(T _(TIP)(t)−T _(TIP)(0))+W ₂*(T _(CENTER)(t)−T(0))−θy(t)=2/(1+exp(−0.002*u(t)))−1 T _(PRED)(t)=150*y(t)+37

[0106] The relationship between y(t) and u(t) is an activation function,which, in the above network 302, is a sigmoidal function. The factor“150” in the last equation is required because of the chosen activationfunction. The term “37” reflects the temperature of the tissue beforeablation, i.e., body temperature. The coefficients are derived based onthe experimental data presented above in Section III(A) with theapparatus shown in FIG. 6

[0107] The weights w₁ and w₂ and the bias term θ(t) were set based upontraining on four experimental sets of data. During the trainingsessions, the weights and bias terms were updated using theback-propagation algorithm described in S. Haykin, “Neural Networks,”IEEE Press (New York), 1994. The final values were computed by averagingthe results in the four training sessions.

[0108]FIG. 11 presents a comparison, for an electrode-tissue angle of90°, of the temperature variations with time, at a constant power of 7W, between actual and predicted maximal tissue temperature. Thecomparison was conducted after the training sessions and with datadifferent than the data used for training, acquired using the apparatusshown in FIG. 6. The comparison shows good correspondence between thetwo control inputs, once overshoot and settling time converge to zero.

B. Prediction Based Upon Fuzzy Logic

[0109] The dependence of maximum tissue temperature on T₁ and T₂ canalso be approximated using fuzzy logic. FIG. 12 shows an alternativeembodiment of the temperature processor 66 which derives P_(DEMAND)using fuzzy logic control principles. In this implementation, theprocessor 66 includes a fuzzifier 502, which receives as inputs thetemperature signals T₁(t) and T₂(t) from the sensing elements 30 and 32.The fuzzifier 502 also receives T_(SET) as input, either as a constantvalue or a value that changes over time. The fuzzifier 502 converts thepairs of T₁(t) and T₂(t) input data to fuzzy inputs based upon referenceto T_(SET) on a relative basis. For example, the fuzzy inputs candetermine the degree (or membership function) to which a given pair ofT₁(t) and T₂(t) is, compared to T_(SET), “cool” or “warm” or “warmer” or“hot”.

[0110] These fuzzy inputs are passed through an I/O mapper 504 whichconverts them to fuzzy outputs by translating the inputs intodescriptive labels of power. This is accomplished, for example, by usinglinguistic “if . . . then” rules, like “if the fuzzy input is . . . thenthe fuzzy output is . . . . ” Alternatively, more complex mappingmatrical operators can be used.

[0111] For example, if the T_(½) pair is “cool,” the I/O mapper 504outputs the descriptive label “Largest Positive,” to indicate that alarge relative increase in power is required. By the same token, if theT_(½) pair is “hot,” the I/O mapper 504 outputs the descriptive label“Largest Negative,” to indicate that large relative decrease in power isrequired. The intermediate fuzzy inputs “warm” and “warmer” produceintermediate descriptive labels as fuzzy outputs, such as “SmallestPositive” and “Smallest Negative.”

[0112] These fuzzy outputs are passed through a defuzzifier 506. Thedefuzzifier 506 also receives actual power P(t) as an input, since thefuzzy outputs refer to variations in P(t). Based upon P(t) and thevariations required based upon the fuzzy outputs, the defuzzifier 506derives P_(DEMAND)(t).

[0113] To define proper reference sets and the rules of the I/O mapper504, it may be required that the fuzzy logic controller be trained on aknown set of data before use.

IV. Other Temperature Sensing Embodiments A. Multiple Electrodes

[0114]FIG. 13 shows a flexible ablating element 74, which includesmultiple, electrode elements, designated E1, E2, and E3 arranged in aspaced apart, segmented relationship along a flexible catheter body 76.The electrode elements can comprise generally rigid electrode rings, orspirally wound lengths of wire (as FIG. 13 shows), or electrode materialcoated upon the body 76.

[0115] As FIG. 13 shows, each electrode element E1, E2, and E3 carriesat least one and, preferably, at least two, temperature sensingelements, designated Si to S6. When the electrode elements exceed about10 mm in length (as FIG. 13 contemplates), the temperature sensingelements S1 to S6 are preferably located at the edges of electrodeelements El to E3, where the electrode elements abut the underlying,non-electrically-conductive catheter body 76. These sensing elements S1to S6 are positioned to sense the temperature of the electrode elements.

[0116] The sensing elements S1 to S6 can be secured to the electrodeelements in various ways. For example, they can be secured to the insidesurface of the electrode elements, or sandwiched between the insidesurface of the electrode and the underlying flexible body.

[0117] Alternatively, the sensing elements S1 to S6 can be threaded upthrough the windings in the electrode elements to lay upon its exteriorsurface.

[0118] Regardless of the particulars, the sensing elements S1 to S6 areelectrically insulated from the electrode elements, such as, forexample, being encapsulated in an epoxy or PTFE coating, as describedbefore.

[0119] As FIG. 13 also shows, additional temperature sensing elements S7and S8 are preferably located between adjacent electrode elements E1 toE3. These temperature sensing elements S7 and S8 are positioned to sensetissue temperature between the electrode elements.

[0120] In this arrangement, each sensing element S7 and S8 is threadedthrough the flexible body between adjacent electrode segments E1 to E3.When the sensing element 80 comprises a thermocouple, an epoxy material,such as Master Bond Polymer System EP32HT (Master Bond Inc., Hackensack,N.J.), encapsulates the thermocouple junction, while also securing it tothe flexible body. Alternatively, the thermocouple junction can becoated in a thin layer of polytetrafluoroethylene (PTFE) material. Whenused in thicknesses of less than about 0.002 inch, these materials havethe sufficient insulating properties to electrically insulate thethermocouple junction from the associated electrode segment E1 to E3.The use of such materials typically will not be necessary whenthermistors are used, because conventional thermistors are alreadyencapsulated in an electrically insulating and thermally conductingmaterial.

[0121] Further details of such multiple electrode structures aredisclosed in copending U.S. application Ser. No. 08/286,930, filed Aug.8, 1994, entitled “Systems and Methods for Controlling Tissue AblationUsing Multiple Temperature Sensing Elements” and itscontinuation-in-part application Ser. No. 08/439,824, filed May. 12,1995, entitled “Systems and Methods for Controlling Tissue AblationUsing Multiple Temperature Sensing Elements.”

[0122] In this embodiment, the temperature acquisition system 64 iscoupled to all temperature sensing elements S1 to S8. The system 64continuously samples at prescribed time periods, t, the analog signalsgenerated by all the sensing elements Si to S8 based upon locally sensedtemperature conditions. The system 64 converts the separate analogsignals of the sensing elements S1 to S8 into individual, proportionaldigital signals. The digital signals from sensing elements S7 and S8located between adjacent electrode elements approximate inter-electrodetissue temperatures T_(n,1)(t), where n identifies a particular one ofthe sensing elements S7 or S8. The digital signals from sensing elementsS1 to S6 located on the electrode elements E1 to E3 correspond toelectrode temperatures T_(k,2)(t), where k identifies a particular oneof the sensing elements S1 to S6.

[0123] In this embodiment, the temperature processing element 66 iscoupled to the temperature acquisition system 64 to receive as input thedigital signal temperatures T_(n,1)(t) and electrode temperaturesT_(k,2)(t). The processing element 66 applies prescribed criteria tothese actual temperature signals to derive, for the sampled timeinterval, a prediction of the hottest tissue temperature contacting eachelectrode element T_(m.pred)(t), where m identifies a particularelectrode element.

[0124]FIG. 17 shows, in schematic form, a representative system 200 forapplying ablating energy by multiple electrodes based, at least in part,upon local temperature conditions sensed by multiple sensing elements.

[0125] In FIG. 17, the multiple sensing elements comprise thermocouples208, 209, and 210 individually associated with multiple electrodes 201,202, and 203. It should be appreciated that more thermocouples couldalso be associated with each electrode (as FIG. 13 shows), and/orthermocouples can be located between electrodes (as FIG. 13 also shows).The system 200 also includes a common reference thermocouple 211 carriedwithin the coupler element 211 for exposure to the blood pool. Thecommon reference thermocouple 211 could also be located externally, forexample, in a catheter handle or in the generator, if maintained thereat a known temperature. Alternatively, other kinds of temperaturesensing elements can be used, like, for example, thermistors, fluoropticsensors, and resistive temperature sensors, in which case the referencesensor 211 would typically not be required.

[0126] The system 200 further includes an indifferent electrode 219 foroperation in a unipolar mode.

[0127] The system 200 includes a source 217 of ablating energy. In FIG.17, the source 217 generates radio frequency (RF) energy. The source 217is connected (through a conventional isolated output stage 216) to anarray of power switches 214, one for each electrode region 201, 202, and203. A connector 212 (carried by the probe handle) electrically coupleseach electrode region 201, 203, 203 to its own power switch 214 and toother parts of the system 200.

[0128] The system 200 also includes a microcontroller 231 coupled via aninterface 230 to each power switch 214. The microcontroller 231 turns agiven-power switch 214 on or off to deliver RF power from the source 217individually to the electrode regions 201, 202, and 203. The deliveredRF energy flows from the respective electrode region 201, 202, and 203,through tissue, to the indifferent electrode 219, which is connected tothe return path of the isolated output stage 216.

[0129] The power switch 214 and interface 230 configuration can varyaccording to the type of ablating energy being applied. FIG. 18 shows arepresentative implementation for applying RF ablating energy.

[0130] In this implementation, each power switch 214 includes an N-MOSpower transistor 235 and a P-MOS power transistor 236 coupled in betweenthe respective electrode region 201, 202, and 203 and the isolatedoutput stage 216 of the power source 217.

[0131] A diode 233 conveys the positive phase of RF ablating energy tothe electrode region. A diode 234 conveys the negative phase of the RFablating energy to the electrode region. Resistors 237 and 238 bias theN-MOS and P-MOS power transistors 235 and 236 in conventional fashion.

[0132] The interface 230 for each power switch 214 includes two NPNtransistors 239 and 240. The emitter of the NPN transistor 239 iscoupled to the gate of the N-MOS power transistor 235. The collector ofthe NPN transistor 240 is coupled to the gate of the P-MOS powertransistor 280.

[0133] The interface for each power switch 214 also includes a controlbus 243 coupled to the microcontroller 231. The control bus 243 connectseach power switch 214 to digital ground (DGND) of the microcontroller231. The control bus 243 also includes a (+) power line (+5V) connectedto the collector of the NPN transistor 239 and a (−) power line (−5V)connected to the emitter of the NPN interface transistor 240.

[0134] The control bus 243 for each power switch 214 further includes anESEL line. The base of the NPN transistor 239 is coupled to the E_(SEL)line of the control bus 243. The base of the NPN transistor 240 is alsocoupled the E_(SEL) line of the control bus 243 via the Zener diode 241and a resistor 232. E_(SEL) line connects to the cathode of the Zenerdiode 241 through the resistor 232. The Zener diode 241 is selected sothat the NPN transistor 240 turns on when E_(SEL) exceeds about 3 volts(which, for the particular embodiment shown, is logic 1).

[0135] It should be appreciated that the interface 230 can be designedto handle other logic level standards. In the particular embodiment, itis designed to handle conventional TTL (transistor transfer logic)levels.

[0136] The microcontroller 231 sets E_(SEL) of the control bus 243either at logic 1 or at logic 0. At logic 1, the gate of the N-MOStransistor 235 is connected to (+) 5 volt line through the NPNtransistors 239. Similarly, the gate of the P-MOS transistor 236 isconnected to the (−) 5 volt line through the NPN transistor 240. Thisconditions the power transistors 235 and 236 to conduct RF voltage fromthe source 217 to the associated electrode region. The power switch 214is “on.”

[0137] When the microcontroller 231 sets E_(SEL) at logic 0, no currentflows through the NPN transistors 239 and 240. This conditions the powertransistors 235 and 236 to block the conduction of RF voltage to theassociated electrode region. The power switch 214 is “off.”

[0138] The system 200 (see FIG. 17) further includes two analogmultiplexers (MUX) 224 and 225. The multiplexers 224 and 225 receivevoltage input from each thermocouple 208, 209, 210, and 211. Themicrocontroller 231 controls both multiplexers 224 and 225 to selectvoltage inputs from the multiple temperature sensing thermocouples 208,209, 210, and 211.

[0139] The voltage inputs from the thermocouples 208, 209, 210, and 211are sent to front end signal conditioning electronics. The inputs areamplified by differential amplifier 226, which reads the voltagedifferences between the copper-wires of the thermocouples 208/209/210and the reference thermocouple 211. The voltage differences areconditioned by element 227 and converted to digital codes by theanalog-to-digital converter 228. The look-up table 229 converts thedigital codes to temperature codes.

[0140] In one preferred implementation, the microcontroller 316 operatesthe power switch interface 230 to deliver RF power from the source 217in multiple pulses of duty cycle 1/N, where N is the number of electrodesegments.

[0141] With pulsed power delivery, the amount of power (P_(E(J)))conveyed to each individual electrode region E(J) is expressed asfollows:

P_(E(J))˜AMP_(E(J)) ²×DUTYCYCLE_(E(J))

[0142] where:

[0143]AMP_(E(J) is the amplitude of the RF voltage conveyed to the electrode region E(J), and)

[0144] DUTYCYCLE_(E(J)) is the duty cycle of the pulse, expressed asfollows:${DUTYCYCLE}_{E{(J)}} = \frac{{TON}_{E{(J)}}}{{TON}_{E{(J)}} + {TOFF}_{E{(J)}}}$

[0145] where:

[0146] TON_(E(J)) is the time that the electrode region E(J) emitsenergy during each pulse period,

[0147] TOFF_(E(J)) is the time that the electrode region E(J) does notemit energy during each pulse period.

[0148] The expression TON_(E(J)) +TOFF_(E(J)) represents the period ofthe pulse for each electrode region E(J).

[0149] In this mode, the microcontroller 231 collectively establishesduty cycle (DUTYCYCLE_(E(J))) of 1/N for each electrode region (N beingequal to the number of electrode regions).

[0150] The microcontroller 231 may sequence successive power pulses toadjacent electrode regions so that the end of the duty cycle for thepreceding pulse overlaps slightly with the beginning of the duty cyclefor the next pulse. This overlap in pulse duty cycles assures that thesource 217 applies power continuously, with no periods of interruptioncaused by open circuits during pulse switching between successiveelectrode regions.

[0151] In this mode, the microcontroller 231 cycles in successive dataacquisition sample periods. During each sample period, themicrocontroller 231 selects individual sensors S(J,K), and voltagedifferences are read by the predictor 290 (through MUX 225) andconverted to temperature codes T_(PRED), which are transmitted to thecontroller 215.

[0152] The predictor 290 receives the temperature codes. In thepreferred implementation, when there are multiple temperature sensingelements on a given electrode element, the predictor selects as T_(k,2)the hottest of the electrode temperatures sensed by the sensing elementson the electrode element. Also, when the electrode element is bounded byboth side by a tissue temperature sensing element, the controllerpredictor also selects as T_(n,1) the hottest of the tissue temperaturessensed by adjacent tissue sensing elements.

[0153] Using the selected values of T_(n,1)(t) and T_(k,2) (t), thepredictor derives T_(M,PRED)(t) in any of the manners above describedfor each electrode element.

[0154] In this mode, the controller 215 compares the predictedtemperature T_(PRED) for each electrode during each data acquisitionperiod to a set point temperature T_(SET). Based upon this comparison,the controller 215 varies the amplitude AMP_(E(J)) of the RF voltagedelivered to the electrode region, while the microcontroller 231maintains the DUTYCYCLE_(E(J)) for that electrode region and all otherelectrode regions, to establish and maintain T_(PRED) at the set pointtemperature T_(SET).

[0155] The manner in which the controller 215 governs AMP_(E(J)) canincorporate proportional control methods, proportional integralderivative (PID) control methods, or fuzzy logic control methods.

B. Self-Heated Temperature Sensing Element

[0156]FIG. 14 shows another alternative embodiment of an electrode 78with multiple temperature sensing elements 80 and 82. In FIG. 14, bothtemperature sensing elements 80 and 82 are connected by soldering or bythermally conducting adhesive to the thermal mass of the electrode 78.

[0157] Alternatively (as FIG. 15 shows), the sensing element 80 can belocated to sense tissue temperature, as sensing element 30 in FIG. 4.

[0158] In addition a resistance heating element 84 is provided for thepurpose of heating the thermal mass of the electrode 78. In theillustrated embodiment shown in FIG. 14, the heating element 84 extendsin intimate contact about the metal steering spring 52. As the heatingspring 52 heats up, the heat is conducted to the thermal mass of theelectrode 78.

[0159] Alternatively (as FIG. 15 shows), the heating element 84 can bewrapped about a portion of the electrode 78 under the catheter body 22.In either embodiment, the heating element 84 is located in good thermalconductive contact with the electrode for ohmic heating of the element84 with DC energy to thereby heat the electrode 78 by conductive heattransfer.

[0160] The heating element 84 can comprise an insulated constantant wirehaving a high resistance, or Nichrome or insulated toaster wire havingthe same characteristic. As FIG. 15 shows, the heating wire 84 is matedwith low resistance copper wire 85 close to the electrode 78. The copperwire 85 extends the rest of the way through the catheter body 22.

[0161] The distance (Δx in FIG. 15) between the two sensing elements 80and 82 should preferably be maximized to the fullest extent possible,given the size of the electrode 78. For example, for an 8F/4 mmelectrode, Δx should be at least 3 mm.

[0162]FIG. 16 shows a system 400 including an electrode 402 having twotemperature sensors TS₁ and TS₂. The electrode 402 also includes theheating element HE 84 heated by the heater 404. The electrode 402 iscoupled to the RF power source 406.

[0163] The temperatures read by TS₁ and TS₂ (T₁ and T₂) are acquired bythe temperature acquisition system 408. The system 400 operates in twophases.

[0164] During this first phase, no ablating energy is directly appliedto the electrode 402. HE is actuated by the heater 404 so that T2 iskept about a set value T_(heat—set). The temperature controller 410which controls the heater 404 can use appropriate control techniques,such as PID, etc.

[0165] During this phase, the temperatures T₁ and T₂ are acquired by theacquisition system 408. The electrical power generated by the heater 404is also measured, P_(heater).

[0166] T₁, T₂ and P_(heater) are inputted to a processing system 412,which, based upon the distance Δx between temperature sensing elementsTS₁ and TS₂ and the whether TS₁ is sensing electrode or tissuetemperature, computes the heat loss, Q_(loss), and the temperaturespatial gradient ΔT/Δx. The processing system 412 can acquireinformation concerning the electrode configuration from the physician,or by a read-only-memory chip and the equivalent associated with theelectrode which the processing system 412 can interrogate. The heatloss, Q_(loss) will depend on the thermal conductivity, density and heatcapacity of the metal of the electrode 402, the amount of electrical andthermal contact between tissue and electrode, and the convective coolinginduced by the blood flow. Therefore, Q_(loss) and ΔT/Δx are indicationsof the present status of the electrical-thermal system at thetissue-electrode-blood interface. This status information is later usedto predict and control the tissue temperature during ablation in thesecond phase.

[0167] In the second phase, ablation energy is applied to tissue throughthe electrode 402. The values of T₁, T₂, Q_(loss), ΔT/Δx, T_(heat—set),and P_(heater) are fed as inputs to a predictor 414.

[0168] The predictor 414 includes in look-up table form relationshipsamong T₁, T₂, Q_(loss), ΔT/Δx, T_(heat—set), P_(heater) and T_(PRED).The inputs to the table are T₁, T₂, Q_(loss), ΔT/Δx,T_(heat—set)P_(heater), and the output of the table is T_(PRED). Thelook-up table is constructed based on experimental data acquired with anapparatus similar to that shown in FIG. 6, using an electrode like thatshown in FIGS. 14 and 15. The table correlates experimentally measuredT₁, T₂, Q_(loss), ΔT/Δx, T_(heat—set), P_(heater) to experimentallymeasured maximum tissue temperature. The output T_(PRED) of the look-uptable is best-fitted to the experimental data.

[0169] The values of Q_(loss), ΔT/Δx, T_(heat—set), P_(heater) takenduring the first phase in connection with T₁ and T₂ characterize thesystem for input to the table. The current status of T₁ and T₂ takenduring the second phase provide from the table a unique outputpredicting the maximal tissue temperature.

[0170] The predictor 414 outputs the predicted tissue temperatureT_(PRED). T_(PRED) and a set temperature value T_(ABL—set) are fed asinputs to a controller 416, which controls the RF power source 406. Thecontroller 416 controls predicted tissue temperature about T_(ABL—set).

[0171] The illustrated and preferred embodiments envision the use ofmicro-processor controlled components using digital processing to,analyze information and generate feedback signals. It should beappreciated that other logic control circuits using micro-switches,AND/OR gates, invertors, and the like are equivalent to themicro-processor controlled components and techniques shown in thepreferred embodiments. It should also be appreciated that the algorithmsdisclosed in this Specification lend themselves to implementation usingeither digital or analog devices.

[0172] Various features of the invention are set forth in the claimsthat follow.

We claim:
 1. An apparatus for heating tissue comprising an electrode totransmit heating energy to a tissue region, a first sensing elementassociated with the electrode for measuring a first temperature, asecond sensing element associated with the electrode for measuring asecond temperature, and a processing element to process one or moretemperatures measured by the first and second sensing elements and toderive therefrom a prediction of maximum temperature of the tissueregion.
 2. An apparatus according to claim 1 wherein the processingelement generates an output based upon the maximum tissue temperatureprediction.
 3. An apparatus according to claim 2 wherein the processingelement generates the output based upon comparing the maximum tissuetemperature prediction to a prescribed temperature.
 4. An apparatusaccording to claim 3 wherein the prescribed temperature remainsessentially constant over time.
 5. An apparatus according to claim 3wherein the prescribed temperature changes at least once as a functionof time.
 6. An apparatus according to claim 3 or 4 or 5 wherein theprocessing element applies at least one proportional, derivative, orintegral coefficient to the comparison of the maximum tissue temperatureprediction to the prescribed temperature to generate the output.
 7. Anapparatus according to claim 1 wherein the processing element controlsthe transmission of heating energy by the electrode based, at least inpart, upon the maximum tissue temperature prediction.
 8. An apparatusaccording to claim 7 wherein the processing element controls thetransmission of heating energy based upon comparing the maximum tissuetemperature prediction to a prescribed temperature.
 9. An apparatusaccording to claim 8 wherein the prescribed temperature remainsessentially constant over time.
 10. An apparatus according to claim 8wherein the prescribed temperature changes at least once as a functionof time.
 11. An apparatus according to claim 8 or 9 or 10 whereinthe-processing element applies at least one proportional, derivative, orintegral coefficient to the comparison of the maximum tissue temperatureprediction to the prescribed temperature to control the transmission ofheating energy.
 12. An apparatus according to claim 1 or 2 or 7 whereinthe electrode transmits radio frequency energy.
 13. An apparatusaccording to claim 1 or 2 or 7 wherein the processing element includes aneural network predictor.
 14. An apparatus according to claim 1 or 2 or7 wherein the processing element derives the maximum tissue temperatureprediction based, at least in part, upon fuzzy logic.
 15. An apparatusaccording to claim 1 or 2 or 7 wherein the processing element processeschanges in temperatures measured by the first and second sensingelements over time to derive the maximum tissue temperature prediction.16. An apparatus according to claim 1 or 2 or 7 wherein the processingelement derives the maximum tissue temperature prediction based, atleast in part, upon an analytical function f(T₁, T₂), where T₁ is thefirst temperature measured by the first sensing element and T₂ is thesecond temperature measured by the second sensing element.
 17. Anapparatus according to claim 1 wherein the electrode carries at leastone of the first and second sensing elements.
 18. An apparatus accordingto claim 17 wherein the at least one sensing element is carried withinthe electrode.
 19. An apparatus according to claim 1 wherein at leastone of the sensing elements is in thermal conductive contact withtissue.
 20. An apparatus according to claim 1 wherein none of thesensing elements is in thermal conductive contact with tissue.
 21. Anapparatus according to claim 1 wherein at least one of the sensingelements is in thermal conductive contact with the electrode.
 22. Anapparatus according to claim 1 wherein at least one of the sensingelements is carried by the electrode within a carrier in thermalconductive contact with tissue.
 23. An apparatus according to claim 22wherein the carrier is made from a thermal conducting material having ahigh thermal conductivity that is at least 1.0 watt (W) per meter (m)Kelvin (K), or 1.0 W/m K.
 24. An apparatus according to claim 1 andfurther including a second electrode spaced along a body from the firstmentioned electrode, and wherein the at least one of the sensingelements is located on the body between the first and second electrodes.25. An apparatus according to claim 24 and further including a thirdtemperature sensing element associated with the second electrode tomeasure a third temperature, and wherein the processing element derivesthe maximum tissue temperature prediction from one or more temperaturesmeasured by the first, second, and third sensing elements.
 26. Anapparatus for ablating body tissue comprising an electrode forcontacting a tissue region to transmit ablation energy, a first sensingelement for measuring temperature of the electrode, a second sensingelement for measuring temperature of tissue contacting the electrode,and a processing element to process one or more temperatures measured bythe first and second sensing elements and to derive therefrom aprediction of maximum temperature of the tissue region.
 27. An apparatusaccording to claim 26 wherein the processing element generates an outputbased upon the maximum tissue temperature prediction.
 28. An apparatusaccording to claim 27 wherein the processing element generates theoutput based upon comparing the maximum tissue temperature prediction toa prescribed temperature.
 29. An apparatus according to claims 28wherein the prescribed temperature remains essentially constant overtime.
 30. An apparatus according to claim 28 wherein the prescribedtemperature changes at least once as a function of time.
 31. Anapparatus according to claims 28 or 29 or 30 wherein the processingelement applies at least one proportional, derivative, or integralcoefficient to the comparison of the maximum tissue temperatureprediction to the prescribed temperature to generate the output.
 32. Anapparatus according to claim 26 wherein the processing element controlsthe transmission of ablation energy by the electrode based, at least inpart, upon the maximum tissue temperature prediction.
 33. An apparatusaccording to claim 32 wherein the processing element controls thetransmission of ablation energy based upon comparing the maximum tissuetemperature prediction to a prescribed temperature.
 34. An apparatusaccording to claim 23 wherein the prescribed temperature remainsessentially constant over time.
 35. An apparatus according to claim 33wherein the prescribed temperature changes at least once as a functionof time.
 36. An apparatus according to claim 33 or 34 or 35 wherein theprocessing element applies at least one proportional, derivative, orintegral coefficient to the comparison of the maximum tissue temperatureprediction to the prescribed temperature to control the transmission ofablation energy.
 37. An apparatus according to claim 26 or 27 or 32wherein the electrode transmits radio frequency energy.
 38. An apparatusaccording to claim 26 or 27 or 32 wherein the processing elementincludes a neural network predictor.
 39. An apparatus according to claim26 or 27 or 32 wherein the processing element derives the maximum tissuetemperature prediction based, at least in part, upon fuzzy logic.
 40. Anapparatus according to claim 26 or 27 or 32 wherein the processingelement processes changes in temperatures measured by the first andsecond sensing elements over time to derive the maximum tissuetemperature prediction.
 41. An apparatus according to claim 26 or 27 or32 wherein the processing element derives the maximum tissue temperatureprediction based, at least in part, upon an analytical function f(T₁,T₂, where T₁ is temperature measured by the first sensing element and T₂is temperature measured by the second sensing element.
 42. An apparatusaccording to claim 26 wherein the electrode carries at least one of thefirst and second sensing elements.
 43. An apparatus according to claim42 wherein the at least one sensing element is carried within theelectrode.
 44. An apparatus according to claim 26 wherein the secondsensing element is carried by the electrode within a carrier in thermalconductive contact with tissue.
 45. An apparatus according to claim 44wherein the carrier is made from a thermal conducting material having ahigh thermal conductivity that is at least 1.0 watt (W) per meter (m)Kelvin (K), or 1.0 W/m K.
 46. An apparatus according to claim 26 andfurther including a second electrode spaced along a body from the firstmentioned electrode, and wherein the second sensing element is locatedon the body between the first and second electrodes.
 47. An apparatusaccording to claim 46 and further including a third temperature sensingelement to measure temperature of the second electrode.
 48. An apparatusfor transmitting energy to an electrode for heating tissue comprising agenerator adapted to be coupled to an electrode to supply energy to theelectrode for heating tissue, a controller coupled to the generator tosupply power to the generator, the controller comprising a first sensingelement associated with the electrode for measuring a first temperature,a second sensing element associated with the electrode for measuring asecond temperature, and a processing element to process one or moretemperatures measured by the first and second sensing elements and toderive therefrom a prediction of maximum temperature of the tissueregion and for generating a signal to control power supplied to thegenerator based, at least in part, upon the maximum tissue temperatureprediction.
 49. An apparatus according to claim 48 wherein theprocessing element controls the transmission of heating energy by theelectrode based, at least in part, upon the maximum tissue temperatureprediction.
 50. An apparatus according to claim 49 wherein theprocessing element controls the transmission of heating energy basedupon comparing the maximum tissue temperature prediction to a prescribedtemperature.
 51. An apparatus according to claim 50 wherein theprescribed temperature remains essentially constant over time.
 52. Anapparatus according to claim 50 wherein the prescribed temperaturechanges at least once as a function of time.
 53. An apparatus accordingto claim 50 or 51 or 52 wherein the processing element applies at leastone proportional, derivative, or integral coefficient to the comparisonof the maximum tissue temperature prediction to the prescribedtemperature to control the transmission of heating energy.
 54. Anapparatus according to claim 48 wherein the electrode carries at leastone of the first and second sensing elements.
 55. An apparatus accordingto claim 54 wherein the at least one sensing element is carried withinthe electrode.
 56. An apparatus according to claim 48 wherein at leastone of the sensing elements is in thermal conductive contact withtissue.
 57. An apparatus according to claim 48 wherein none of thesensing elements is in thermal conductive contact with tissue.
 58. Anapparatus according to claim 48 wherein at least one of the sensingelements is in thermal conductive contact with the electrode.
 59. Anapparatus according to claim 48 wherein at least one of the sensingelements is carried by the electrode within a carrier in thermalconductive contact with tissue.
 60. An apparatus according to claim 59wherein the carrier is made from a thermal conducting material having ahigh thermal conductivity that is at least 1.0 watt (W) per meter (m)Kelvin (K), or 1.0 W/m K.
 61. An apparatus according to claim 48 andfurther including a second electrode spaced along a body from the firstmentioned electrode, and least one proportional, derivative, or integralcoefficient to the comparison of the maximum tissue temperatureprediction to the prescribed temperature to generate the output.
 74. Anapparatus according to claim 63 wherein the electrode carries at leastone of the first and second sensing elements.
 75. An apparatus accordingto claim 74 wherein the at least one sensing element is carried withinthe electrode.
 76. An apparatus according to claim 63 wherein the secondsensing element is carried by the electrode within a carrier in thermalconductive contact with tissue.
 77. An apparatus according to claim 76wherein the carrier is made from a thermal conducting material having ahigh thermal conductivity that is at least 1.0 watt (W) per meter (m)Kelvin (K), or 1.0 W/m K.
 78. An apparatus according to claim 63 andfurther including a second electrode spaced along a body from the firstmentioned electrode, and wherein the second sensing element is locatedon the body between the first and second electrodes.
 79. An apparatusaccording to claim 78 and further including a third temperature sensingelement to measure temperature of the second electrode.
 80. An apparatusaccording to claim 48 or 63 wherein the electrode transmits radiofrequency energy.
 81. An apparatus according to claim 48 or 63 whereinthe processing element includes a neural network predictor.
 82. Anapparatus according to claim 48 or 63 wherein the processing elementderives the maximum tissue temperature prediction based, at least inpart, upon fuzzy logic.
 83. An apparatus according to claim 48 or 63wherein the processing element processes changes in temperaturesmeasured by the first and second sensing elements over time to derivethe maximum tissue temperature prediction.
 84. An apparatus according toclaim 48 or 63 wherein the processing element derives the maximum tissuetemperature prediction based, at least in part, upon an analyticalfunction f(T₁, T₂), where T₁ is the temperature measured by the firstsensing element and T₂ is the temperature measured by the second sensingelement.
 85. A method for heating body tissue comprising positioning anelectrode to trannsmit heat energy to a tissue region, measuring a firsttemperature using a temperature sensing element associated with theelectrode, measuring a second temperature using a temperature sensingelement associated with the electrode, and processing at least one ofthe first and second temperatures to derive a prediction of maximumtemperature of the tissue region.
 86. A method according to claim 85 andfurther including the step of generating an output based upon themaximum tissue temperature prediction.
 87. A method according to claim86 wherein the output is based upon comparing the maximum tissuetemperature prediction to a prescribed temperature.
 88. A methodaccording to claim 87 wherein the prescribed temperature remainsessentially constant over time.
 89. A method according to claim 87wherein the prescribed temperature changes at least once as a functionof time.
 90. A method according to claim 87 or 88 or 89 wherein theprocessing step applies at least one proportional, derivative, orintegral coefficient to the comparison of the maximum tissue temperatureprediction to the prescribed temperature to generate the output.
 91. Amethod according to claim 85 wherein the processing element controls thetransmission of heating energy by the electrode based, at least in part,upon the maximum tissue temperature prediction.
 92. A method accordingto claim 91 wherein the processing element controls the transmission ofheating energy based upon comparing the maximum tissue temperatureprediction to a prescribed temperature.
 93. A method according to claim92 wherein the prescribed temperature remains essentially constant overtime.
 94. A method according to claim 92 wherein the prescribedtemperature changes at least once as a function of time.
 95. A methodaccording to claim 92 or 93 or 94 wherein the processing element appliesat least one proportional, derivative, or integral coefficient to thecomparison of the maximum tissue temperature prediction to theprescribed temperature to control the transmission of heating energy.96. A method according to claim 85 wherein the electrode transmits radiofrequency energy.
 97. A method according to claim 85 wherein theprocessing step includes a neural network predictor.
 98. A methodaccording to claim 85 wherein the processing step derives the maximumtissue temperature prediction based, at least in part, upon fuzzy logic.99. A method according to claim 85 wherein the processing step processeschanges in temperatures measured by the first and second sensingelements over time to derive the maximum tissue temperature prediction.100. A method according to claim 85 wherein the processing elementderives the maximum tissue temperature prediction based, at least inpart, upon an analytical function f(T₁, T₂), where T₁ is the firsttemperature measured by the first sensing element and T₂ is the secondtemperature measured by the second sensing element.
 101. A method forablating body tissue comprising placing an electrode in contact with atissue region to transmit ablation energy, measuring a first temperatureof the electrode, measuring a second temperature of tissue contactingthe electrode, and processing at least one of the first and secondtemperatures a prediction of maximum temperature of the tissue region.102. A method according to claim 101 wherein the processing stepgenerates an output based upon the maximum tissue temperatureprediction.
 103. A method according to claim 102 wherein the processingstep generates the output based upon comparing the maximum tissuetemperature prediction to a prescribed temperature.
 104. A methodaccording to claim 103 wherein the prescribed temperature remainsessentially constant over time.
 105. A method according to claim 103wherein the prescribed temperature changes at least once as a functionof time.
 106. A method according to claim 103 or 104 or 105 wherein theprocessing step applies at least one proportional, derivative, orintegral coefficient to the comparison of the maximum tissue temperatureprediction to the prescribed temperature to generate the output.
 107. Amethod according to claim 101 wherein the processing step controls thetransmission of ablation energy by the electrode based, at least inpart, upon the maximum tissue temperature prediction.
 108. A methodaccording to claim 107 wherein the processing step controls thetransmission of ablation energy based upon comparing the maximum tissuetemperature prediction to a prescribed temperature.
 109. A methodaccording to claim 108 wherein the prescribed temperature remainsessentially constant over time.
 110. A method according to claim 108wherein the prescribed temperature changes at least once as a functionof time.
 111. A method according to claim 108 or 109 or 110 wherein theprocessing atwp applies at least one proportional, derivative, orintegral coefficient to the comparison of the maximum tissue temperatureprediction to the prescribed temperature to control the transmission ofablation energy.
 112. A method according to claim 101 wherein theelectrode transmits radio frequency energy.
 113. A method according toclaim 101 wherein the processing step includes a neural networkpredictor.
 114. A method according to claim 101 wherein the processingstep derives the maximum tissue temperature prediction based, at leastin part, upon fuzzy logic.
 115. A method according to claim 101 whereinthe processing step processes changes in temperatures measured by thefirst and second sensing elements over time to derive the maximum tissuetemperature prediction.
 116. A method according to claim 101 wherein theprocessing step derives the maximum tissue temperature prediction based,at least in part, upon an analytical function f(T₁, T₂), where T₁ istemperature measured by the first sensing element and T₂ is temperaturemeasured by the second sensing element.